Data from the U.S. Bureau of Labor Statistics indicates the representation of women in computer and mathematical operations is slightly worse than it was in 2010, and the same holds true for the field of software developers. Research suggests diverse corporate teams make better decisions and are financially better off. Technology firms' efforts to address the issue of low numbers of women employees was underscored at the annual Grace Hopper Celebration of Women in Computing conference. The event featured 148 companies, 57 academic institutions, and 22 labs. Government and nonprofit organizations recruited from a pool of about 7,000 women working in technical roles and about 3,600 students. University of Wisconsin-Milwaukee's Nadya Fouad presented her findings on why large numbers of female engineers were leaving their jobs. She had surveyed 5,300 women who graduated with engineering degrees between 1980 and 2010, and found many left their jobs due to such things as inadequate manager support and lack of opportunities for advancement. One strategy for connecting diversity to long-term business interests is to set clear goals, and one such company at Grace Hopper was ThoughtWorks, with a staff of about 3,500 people across 13 countries that specializes in software consulting, delivery, and products.

As robotics researchers seek to develop more sophisticated and natural means for humans to interact with robots, they are also seeking to develop systems that will ensure these interactions do not prove dangerous for the robots. Gordon Briggs and Matthias Scheutz of Tufts University's Human-Robot Interaction Lab are working specifically on techniques that will enable robots to reject orders from humans that could prove dangerous to the robots. The system borrows the concept of "felicity conditions" from linguistic theory, which reflect a person's understanding of and capability to fulfill instructions. Briggs and Scheutz's system is designed to create a framework that allows a robot to utilize felicity conditions to determine whether it is able to carry out instructions it receives, and whether or not it should do so. For example, the system will enable the robot to refuse an order to walk forward if it detects that doing so will cause it to run into a wall or off a table. The system also allows human operators to clarify their commands after they have been rejected, such as by saying that they will catch the robot if it falls. Briggs and Scheutz' research was presented at the AI for Human-Robot Interaction Symposium in Washington, D.C., earlier this month.

Researchers Confirm 'Realistic' Answer to Quantum Network PuzzleUniversity of York (11/19/15) David Garner

New research from the University of York supports the development of scalable and secure high-rate quantum networks. Scientists from York's Center of Quantum Technology have compared the state of the art in continuous variable systems with the standard discrete variable systems. "If you want to build a metropolitan network based on quantum cryptography, you need a high-rate, super-fast connection, otherwise you can't compete with the classical communication infrastructure," says York computer scientist Stefano Pirandola. The researchers report the use of cryogenic devices and standard Quantum Key Distribution (QKD) is unlikely to approach the high rates achieved both theoretically and experimentally using a continuous variable quantum system. The problem with QKD protocols based on simple quantum systems is their low key-rate, which makes them unsuitable for adaptation for use in metropolitan networks. On the other hand, continuous variable systems allow the parallel transmission of many qubits of information while retaining the quantum capability of detecting and defeating eavesdroppers. The researchers say continuous variable systems offer the best and least expensive technology and can work at room temperature.

The Massachusetts Institute of Technology's (MIT) Department of Electrical Engineering and Computer Science (EECS) hosts "Rising Stars in EECS," a three-day workshop for female graduate students and postdocs considering careers in academic research. Founded in 2012 by EECS director and professor Anantha Chandrakasan, Rising Stars offers women in EECS learn-by-doing experiences, with sessions concentrating on securing a faculty job, attaining tenure, and building a professional support network. "We hope to give them the information they need to be successful as they explore job opportunities," says Chandrakasan. "But we also feel very strongly about giving participants a chance to get to know each other and make lasting connections. These connections can open doors for collaborations and provide professional support for years to come." Many participants were linked by the common story of being only one of a small number of women at their home lab. "This workshop is designed to be a professional launching pad," notes MIT Chancellor Cynthia Barnhart. She cites many advantages of an academic career, including the freedom to stretch and grow across disciplines, the opportunity to perform original research, and the chance to mentor and inspire other students, including women.

Network Time Protocol (NTP) is necessary for the Internet to function, but is also linked to distributed denial of service (DDoS) attacks. Consequently, the NTP Security Project has released it first public development of NTPsec, which will be ready for production use within a few months. Previously NTP's documentation was both incomplete and years out of date, which hurt NTP's ability to bring additional developers to relate its problems. NTP's aging codebase's maintainability and security have been significantly improved. The NTPSec beta, NTPsec 0.9, is now ready for open source developers to work with and for feedback from government, corporate, and academic software and information technology labs, and will soon be ready for widespread use. "Most of the changes are under the hood and not user-visible," says lead project developer Eric S. Raymond. "The most important change you can't see is that the code has been very seriously security-hardened, not only by plugging all publicly disclosed holes but by internal preventive measures to close off entire classes of vulnerabilities." In the meantime, system administrators are encouraged to update to the latest version of NTP; if they have access to their network's firewall, they also should implement BCP38's Ingress and Egress filtering to help prevent NTP servers from being used in DDoS attacks.

Clothes Smarter Than You Are: Welcome to the FuturePhys.Org (11/19/15) Sebastian Smith

Massachusetts Institute of Technology (MIT) Media Lab researcher Marcelo Coelho concentrates on developing wearable devices whose intelligence may exceed that of their wearer. He envisions clothes programmed to change color or patterns, dresses with hemlines that automatically rise and fall, and other smart textiles enabled by integrated computers. Coelho has developed a watch-shaped device equipped with a small computer that is programmed with the user's personal data, which also communicates with other devices in a room. This device can signal if other people in the room have things in common with the wearer, pointing toward opportunities to socialize. Dovetailing with this concept is fellow MIT scientist Skylar Tibbits' focus on fourth-dimensional printing, in which three-dimensional printers can arrange and configure themselves in novel and useful ways, using materials that change in a pre-determined manner in response to ordinary forces such as pressure or water. "They are materials that behave like robots, but don't need robots," Tibbits says. "We eventually propose that the materials could assemble themselves from scratch." Further out, Coelho anticipates chips and Wi-Fi devices implanted directly into the human body.

How to Pick Out a Face in the CrowdSydney Morning Herald (Australia) (11/17/15) Melinda Ham

A computer scientist from Sydney's University of Technology and colleagues have addressed the accuracy limitations of existing facial recognition technology. Dacheng Tao, from the university's Center for Quantum Computation & Intelligent Systems, describes the team's new algorithm as a major breakthrough. "Since computers calculate measurements on the face numerically, it's widely acknowledged that different facial expressions--if you smile or are angry, if the image is not frontal, even if you wear make-up and glasses and if the lighting is different--can affect these statistical features when comparing photos with one another," Tao says. The new algorithm is designed to measure the center of the eyes, the peak of the nose, and the corners of the mouth. Tao notes the five facial points are strong, stable, and change little in different environments. He says the algorithm is based on multi-modal deep learning. The process involves taking the points from a two-dimensional image and extracting robust statistical features for subsequent recognition of a subject.

A new study from a group of researchers in Austria shows programmers who participate in open source projects are motivated by a different set of values than money. The team surveyed software package developers involved in the R environment for statistical computing. Among project developers, the researchers found purely intrinsic motivations such as personal satisfaction and purely extrinsic motivations such as receiving compensation to be less important. They found the work design characteristics of the R project to be a strong determinant for programmers making contributions. Interactions with persons perceived as important within the community contributed to personal reputation and interaction with like-minded people contributed to social inclusion. "The R community seems to offer the opportunity for R developers to identify with this highly valued group and feel a sense of belonging," say the authors of the study. They also note task characteristics can influence participation. For example, if a project's central task is developing an R package, programmers were more likely to contribute.

Numerous academic research projects around the U.S. and beyond rely on high-performance computing (HPC) resources funded by the U.S. National Science Foundation (NSF). The iPlant Collaborative has developed a cyberinfrastructure for life science research that is providing insights into the genetic traits of crops, while the nanoHUB portal is doing similar work in the space of nanomaterials. The NSF-funded Blue Waters supercomputer located at the National Center for Supercomputing Applications is being used by a variety of academic research programs, including the Southern California Earthquake Center and a joint NSF-National Geospatial-Intelligence Agency project to develop high-resolution Digital Elevation Models of the Arctic. Wake Forest University's Center for Injury Biomechanics is using the Blacklight supercomputer at the Pittsburgh Supercomputing Center to simulate the effects of car crashes on human bodies. Advanced LIGO, an ambitious project to revamp the way that astronomical data is captured and shared among researchers, is utilizing the assets of XSEDE, an NSF collection of HPC resources and services. The Texas Advanced Computing Center (TACC) is using NSF funding to pursue a number of projects, including educational initiatives aimed at training the next generation of HPC professionals, and a project to build up the supercomputing community in South Africa, Tanzania, and Botswana in part by relocating a decommissioned TACC supercomputer.

Managing the Data Deluge for National Security AnalystsSandia National Laboratories (11/17/15) Heather Clark

Sandia National Laboratories' Pattern Analytics to Support High-Performance Exploitation and Reasoning (PANTHER) team has made several breakthroughs that could help solve problems associated with the massive amount of data that is growing faster than analysts' ability to observe and process it. The PANTHER team has been able to rethink how to compare motion and trajectories, develop software that can represent remote sensor images, and conduct fundamental research on visual cognition, according to PANTHER's Kristina Czuchlewski. The project's fundamental research in cognitive science will inform the design of software and tools to help those viewing the data. "PANTHER developed the foundation for transforming how massive, complex data sets can be quickly analyzed to provide the nation's decision-makers with new perspectives on situations and circumstances," says Sandia's Anthony Medina. For example, Sandia researchers developed the Tracktable code to automate the observation of motion and trajectories. The PANTHER researchers also examined the predictive capability of the information buried in data. The team currently is studying integrating motion and trajectories into a software system called GeoGraphy, which converts remote-sensing images expressed in pixels into nodes and edges in a graph to show changes over time and make data searchable. GeoGraphy breaks images into categories, and then uses nodes and edges to describe relationships between objects.

Harvard University's breakthrough RoboBee robots can fly, land, and swim in a preprogrammed trajectory, and giving them vision is the next step in their evolution. Researchers at the University of Florida (UF) and the State University of New York at Buffalo (SUNY Buffalo) received a $1.1-million U.S. National Science Foundation (NSF) grant to miniaturize lidar (light detection and ranging) technology so the RoboBees can self-navigate. The small size of the robot drones makes using conventional cameras impossible, according to SUNY Buffalo researcher Karthik Dantu. With the NSF grant, Dantu is developing mathematical algorithms that will work in tandem with lightweight sensors designed by UF researcher Sanjeev Koppal so the sensors can optimize how they use the data they capture. Laser emitters built by UF's Huikai Xie will complete the package. The researchers will initially employ a mirror with wide-angle optics on the RoboBee to collect laser pulses from a remote lidar base station, and refine the appropriate algorithm for the sensors with that data. They then will mount a laser diode on the drone itself tethered to a base station or battery, prior to implementing internal powering. Potential uses of the drones include endoscopic probes for internal body imaging, monitoring air pollution via robot swarms, and search-and-rescue missions.

Researchers at the University of Southern California (USC) and Medable have created Biogram 2, a program designed to help scientists study health on a global scale by enabling users to share photos and post their heart rate through Apple's ResearchKit. USC researchers can then examine anonymous heart rates and understand health all over the world. Biogram's interface is similar to Instagram, but instead of posting photos, users are asked to include their heart rate. "One of the ways we can start to make fundamental breakthroughs in healthcare is by collecting biometric data in large so we can really understand major public health issues and events," says USC Center for Body Computing executive director Leslie Saxon. The researchers hope to utilize something that people are already doing in posting photos, and to capture them in the moment so it is a natural, non-additional experience, according to Medable's Ingid Oakley-Girvan. The researchers want to use the biometric data to help people educate themselves about their own health and draw correlations between photo sharing and heart rate. "I'm interested in how heart rate reflects how people feel about sharing and how others respond [by liking posts]," Saxon says.